Data packet prioritization for downlink transmission at sender level

ABSTRACT

Techniques for network-based and sender-based data packet prioritization for downlink transmissions are discussed herein. Packets can be tagged or associated with information indicative of a priority of the packet for downlink transmission to a user equipment (UE). A priority level can be determined based on an application identifier or type associated with a data request, a level of user interaction with the UE, network conditions, and other factors. Packets can be received by a PDCP layer of a base station for sending based on the priority. Packets may be associated with a primary priority level associated with a QCI level and a secondary priority level based on UE and/or network factors discussed herein. Packets associated with a same QCI may be prioritized to optimize transmission of downlink data associated with a single UE or between transmission of downlink data associated with a plurality of UEs.

BACKGROUND

Cellular communication devices use network radio access technologies tocommunicate wirelessly with geographically distributed cellular basestations. Long-Term Evolution (LTE) is an example of a widelyimplemented radio access technology that is used in 4th-Generation (4G)communication systems. New Radio (NR) is a newer radio access technologythat is used in 5th-Generation (5G) communication systems. Standards forLTE and NR radio access technologies have been developed by the 3rdGeneration Partnership Project (3GPP) for use by wireless communicationcarriers.

Mobile devices and base stations have radio protocol stacks that handledetails of wireless data transmissions for standalone and dualconnectivity communications. For example, data may be provided by anapplication, packetized to create data packets, and further processed byvarious layers of the radio protocol stack before being transmittedwirelessly as uplink data. Similarly, data may be provided by a datasource to a base station as packetized data and transmitted to mobiledevices as downlink data.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is described with reference to the accompanyingfigures. In the figures, the left-most digit(s) of a reference numberidentifies the figure in which the reference number first appears. Theuse of the same reference numbers in different figures indicates similaror identical components or features.

FIG. 1 shows an example network environment in which a user equipment(UE) can connect to a telecommunication network to receive downlink dataprioritized in accordance with the techniques discussed herein.

FIG. 2 is a block diagram of a UE including components for determiningattributes for prioritizing downlink data.

FIG. 3 is a block diagram of a device including components forprioritizing downlink data for a UE based on various factors.

FIG. 4 is a block diagram of a device including various layers of aradio protocol stack including one or more queues for prioritizingdownlink data.

FIG. 5 shows a sequence diagram of example operations and messages fornetwork-based data packet prioritization for downlink transmission.

FIG. 6 shows a sequence diagram of example operations and messages forsender-based data packet prioritization for downlink transmission.

FIG. 7 illustrates an example process for network-based data packetprioritization for downlink transmission.

FIG. 8 illustrates an example process for sender-based data packetprioritization for downlink transmission.

FIG. 9 illustrates an example process for implementing inter-UE downlinkdata prioritization and/or intra-UE downlink data prioritization.

DETAILED DESCRIPTION

Techniques for network-based and sender-based data packet prioritizationfor downlink transmissions are discussed herein. For example, InternetProtocol (IP) data packets can be tagged or otherwise associated withinformation indicative of a priority of the data packet for downlinktransmission to a user equipment (UE). The data packets can be receivedby a Packet Data Convergence Protocol (PDCP) layer of a base station forqueuing and/or transmission to other layers of a radio protocol stackbased on a designated priority. In some examples, a packet may beassociated with a primary priority level associated with a Quality ofService (QoS) Class Identifier (QCI) level and a secondary prioritylevel based on factors discussed herein. Packets associated with a sameQCI may be prioritized to optimize transmission of downlink dataassociated with a single UE or between transmission of downlink dataassociated with a plurality of UEs.

The data packet prioritization can be based on attributes associatedwith a UE. For example, a priority level can be based on a type of datatraffic, such as web browsing, streaming (e.g., videos, music, etc.),gaming, and the like. In some examples, a priority level can be based atleast in part on an application identifier associated with a datarequest. For example, a UE can transmit a data request to a data source,whereby the data request comprises an application identifier associatedwith the data request. The data request can be analyzed to determine theapplication identifier associated with the data request and packetsprovided in response to the request can be prioritized based on theapplication identifier.

In some examples, prioritization factors can include, but are notlimited to, an application identifier, an indication of whether theapplication is in a foreground of a display or a background of adisplay, a destination IP address associated with a data request, asubscriber level associated with a UE or a user profile, deep packetinspection to determine packet type, location data of the UE, UE devicetype data, user preferences, power characteristics (e.g., battery powerlevel) associated with the UE, aggregated user data or historical data,and the like. Prioritization factors can further include a QCI levelassociated with a data request, an amount of data traffic and/orcongestion (e.g., relative to a data traffic level or a congestionlevel) associated with one or more base stations, base stationcharacteristics (e.g., an availability of a Fifth Generation (5G) NewRadio (NR) base station, an availability of a Fourth Generation (4G)Long-Term Evolution (LTE) base station), and the like.

In some examples, data associated with a data request can be received bya computing device comprising a model to determine a priority levelassociated with data packets. For example, the computing device cancomprise a machine learned model that is trained to determine a prioritylevel associated with data packets in response to a data request andbased on prioritization factors, as discussed herein. In some examples,a UE can include a model (e.g., a machine learned model) and can providean indication of a determined priority level associated with a datarequest to a base station and/or to a data source. Data packets can betagged or otherwise associated with the priority level in anetwork-based implementation and/or in a sender-based implementation.

In a network-based implementation of the prioritization techniquesdiscussed herein, the machine learned model can determine a prioritylevel and provide an indication of the priority level to a PDCP layer ofa base station. When the PDCP layer receives data packets in response toa data request from a UE, the PDCP layer can tag or otherwise associatethe data packets with the priority level for downlink transmission tothe UE. The PDCP layer can provide the packets to other layers of aradio protocol stack, such as a Radio Link Control (RLC) layer, a MediumAccess Control (MAC) layer, and a Physical (PHY) layer for transmissionto a UE. In some examples, the PDCP layer can provide packets to anotherPDCP layer of another base station (e.g., in a dual connectivitycontext).

In a sender-based implementation of the prioritization techniquesdiscussed herein, the machine learned model can determine a prioritylevel and provide an indication of the priority level to a data sourceassociated with the data request. For example, a UE can send a datarequest to a data source. A prioritization model (e.g., a model such asa machine learned model at the UE, a computing device, a base station,or the data source) can determine a priority level for packetsassociated with the data request and can provide an indication of thepriority level to the data source. The data source can tag or otherwiseassociate the data packets with the priority level and can send thetagged data packets to a base station for transmission to the UE inaccordance with the priority level. The tagged data packets may bereceived by a PDCP layer of a base station and can be provided to otherlayers of the radio protocol stack (or another PDCP layer of anotherbase station) for transmission to the UE.

In some examples, the prioritization techniques discussed herein may betreated as a preference or priority, rather than an unbreakable rule.Other factors, for example, might affect the routing of a data packet,such as signal availability, buffer capacity, the current performance ofa base station, the priority of other UEs and/or data packets to besent, an amount of time a data packet has been in a transmission queue,and so forth.

As noted above, in some examples, the priority level may be associatedwith data packets as a packet tag. In some examples, the PDCP layer maycompare the packet tags of a data packet to a preconfigured policy thatspecifies relative priorities for different applications and customers.Data packets from high-priority sources may then be given preference inbuffer overflow conditions. Specifically, although some queued datapackets may time out and be discarded to prevent buffer overflow,preferred or prioritized packets may be retained in transmission queuesregardless of timeout parameters. In some examples, data can beassociated with various queues associated with a PCDP layer, asdiscussed herein.

In some examples, a transmission of packets to a UE can be based on thepacket tags in the absence of congestion or buffer overflow conditions.For example, the packet tags can be used to prioritize data associatedwith a same UE to optimize downlink traffic to the UE without regard todownlink traffic associated with other UEs.

In some cases, a packet tag can indicate whether the packet should betransmitted using an LTE connection or an NR connection of aNon-Standalone (NSA) architecture or other dual connectivity session. Insome implementations, this determination may be based on a policy thathas been preconfigured to specify either LTE or NR transmission fordifferent applications and/or customers. The policy may be based onneeds of different applications and the different characteristics of LTEand NR communications. In some systems, LTE may be considered to providehigher reliability than NR, as an example. Similarly, NR may beconsidered to provide higher bandwidth and lower latency than LTE. Insome systems, data packets from applications that may need highreliability, such as email applications, may be transmitted using LTE.Data packets associated with applications such as gaming applications,for example, which may need low latency, may be transmitted using NR.Applications needing high throughput, such as video applications, may bealso be transmitted using NR.

The techniques discussed herein can be used to implement intra-UEprioritization and/or inter-UE prioritization. In some instances,intra-UE prioritization can be used to prioritize downlink transmissionsamong transmissions associated with a single UE while inter-UEprioritization can be used to prioritize downlink transmissions amongvarious UEs. By way of example and without limitation, for a UErequesting first data associated with a gaming application, second dataassociated with a streaming music application, and third data associatedwith a file download, requests associated with each of the data may beassociated with a same QCI. However, a model such as a machine learnedcomponent can receive prioritization factors associated with the UE andcan prioritize packets associated with the first, second and third datapackets, respectively, to provide a high Quality of Experience (QoE) toa user. For example, the gaming application may be in the foreground ofa display of the UE, which may contribute to a high priority of packetsassociated with the first data. In some cases, the second dataassociated with streaming music may have a higher priority than thethird data, while in some examples, the third data associated with afile download may be prioritized above the second data to minimize anamount of time to download the file. The priority levels can bedetermined based on UE attributes, network attributes, user preferences,and the like, as discussed herein.

The described techniques enhance network functionality and userexperience by customizing the transmission of data to provide the mostappropriate performance characteristics for any particular applicationor customer.

The techniques discussed herein can be implemented in the context ofprotocols associated with one or more of 3G, 4G, 4G LTE, and/or 5Gprotocols. In some examples, the network implementations can supportstandalone architectures, non-standalone architectures, dualconnectivity, carrier aggregation, etc. Example implementations areprovided below with reference to the following figures.

FIG. 1 shows an example network environment 100 in which a userequipment (UE) 102 can connect to a telecommunication network to receivedownlink data prioritized in accordance with the techniques discussedherein. The UE 102 can be any device that can wirelessly connect to thetelecommunication network. In some examples, the UE 102 can be a mobilephone, such as a smart phone or other cellular phone. In other examples,the UE 102 can be a personal digital assistant (PDA), a media player, atablet computer, a gaming device, a smart watch, a hotspot, a personalcomputer (PC) such as a laptop, desktop, or workstation, or any othertype of computing or communication device.

The UE 102 can include a reporting component 104 that can determineattributes associated with the UE can that be used to determine apriority level associated a data request. In some examples, thereporting component 104 can determine a priority level associated with adata request and can include an indication of that priority level to beprovided to a computing device such as a base station 106, a computingdevice 108, and/or a computing device 110. In general, the reportingcomponent 104 can gather or otherwise determine attributes of the UE102, such as an application identifier, user behavior, a state of theUE, indication(s) of user preferences (e.g., express via a userinterface or implied via observed/learned behavior), and the like. Insome examples, the reporting component 104 may include heuristics,policies, rules, and/or models (e.g., machine learned models) todetermine a priority level associated with a data request. In someexamples, the reporting component 104 may gather or otherwise determineattributes associated with the UE 102 and provide such attributes toother devices, as discussed herein. Additional details of the UE 102 andthe reporting component 104 are discussed in FIG. 2, as well asthroughout this disclosure.

The telecommunication network can have one or more access networks thatinclude base stations (e.g., the base station 106) and/or other accesspoints, as well as a core network linked to the access network. Theaccess networks and/or the core network can be compatible with one ormore radio access technologies, wireless access technologies, protocols,and/or standards, such as 5G NR technology, LTE/LTE Advanced technology,other Fourth Generation (4G) technology, High-Speed Data Packet Access(HSDPA)/Evolved High-Speed Packet Access (HSPA+) technology, UniversalMobile Telecommunications System (UMTS) technology, Code DivisionMultiple Access (CDMA) technology, Global System for MobileCommunications (GSM) technology, WiMAX technology, Wi-Fi technology,and/or any other previous or future generation of radio accesstechnology.

The UE 102 can wirelessly connect to the base station 106 and can senddata requests to a data source, such as the computing device 110comprising data 112. In conjunction with or based at least in part on adata request, the UE 102 can send attribute data and/or priority data tothe computing device 108 (e.g., in a case where a prioritizationcomponent 114 is implemented in the computing device 108) or to anotherdevice comprising the prioritization component 114. In some examples,the base station 106 can receive at least a portion of the data 112 aspacketized data. In the case of the network-based prioritization ofdownlink data transmission, the base station 106 can tag or otherwiseassociate a priority level with data packets received from the computingdevice 110. In the case of a sender-based prioritization of downlinkdata transmission, the computing device 110 can tag or otherwiseassociate a priority level with data packets to be sent to the basestation 106.

The base station 106 can include queue(s) 116, whereby data received bythe base station 106 can be input to the queue(s) 116 for transmissionto the UE 102. In some examples, the queue(s) 116 can be associated witha PDCP layer of a radio protocol stack. In some examples, the queue(s)116 can include a plurality of queues with different destinations,priority levels, sizes, delay characteristics, packet error loss rates,and the like. In some examples, the queue(s) 116 can individual queuesassociated with specific data bearers, such as a dedicated bearer, adefault bearer, and the like. In some examples, data input to a queue ofthe queue(s) 116 may be transmitted in a first-in first-out (FIFO)manner. However, in some examples, data can be added to a queue based ona priority level associated with such data and/or data can be reorderedor transmitted from the queue based on the priority level, therebydeviating somewhat from the FIFO transmission scheme. Additionaldiscussion of queues is provided in connection with FIG. 4, as well asthroughout this disclosure.

In some examples, the base station 106 can be implemented in the contextof an LTE access network known as an Evolved UMTS Terrestrial RadioAccess Network (E-UTRAN). Base stations of the LTE access network can beknown as eNBs. The base station 106 can also be implemented in thecontext of 5G access network with base stations known as gNBs. In someexamples, the base station 106 can represent an eNB and a gNB located ata same cell site. In other examples, the base station 106 can representan eNB and a gNB located at different cell sites.

The base station 106 can be implemented to support dual connectivitybetween the UE 102 and multiple base stations in an access network. Forexample, the UE 102 can establish an LTE connection with an eNB and a 5Gconnection with an gNB, where such a connection can be referred to as anE-UTRAN New Radio-Dual Connectivity (EN-DC) connection. An EN-DCconnection may be based on a 3GPP EN-DC configuration, such as an“option 3x” EN-DC configuration, “option 3” EN-DC configuration, “option3a” EN-DC configuration, or other EN-DC configuration.

The UE 102 may connect to a core network via one or more bearers.Bearers can be virtual channels used to transport data for the UE 102between network elements. For example, a data radio bearer may beestablished between the base station 106 and the UE 102. When thetechniques are implemented in an intra-UE context, data packets can beprioritized with respect to a single bearer (or with respect to multiplebearers in the context of dual connectivity) associated with a singleUE. In such cases, a single UE can be associated with a single queue ofthe queue(s) 116. When techniques are implemented in an intra-UEcontext, the queue(s) 116 can be associated with multiple UEs such thatprioritizing data packets may prioritize data packets for a first UEover a second UE that is different than the first UE.

FIG. 2 is a block diagram of a UE 200 including components fordetermining attributes for prioritizing downlink data. In some examples,the UE 200 (also referred to as a device 200) can be configured toimplement some or all of the techniques discussed herein.

FIG. 2 shows basic, high-level components of the device 200. Generally,the device 200 may comprise and/or may be implemented in any of variousnetwork components discussed herein, including those componentsillustrated in FIG. 1.

In various examples, the device 200 may include processor(s) 202 andmemory 204. Depending on the exact configuration and type of computingdevice, the memory 204 may be volatile (such as RAM), non-volatile (suchas ROM, flash memory, etc.) or some combination of the two. The memory204 may include the reporting component 104, which may include anapplication ID 206, user preference(s) 208, IP address(es) 210, and/orUE state data 212, and a machine learned component 214.

In some examples, the reporting component 104 can include functionalityto gather or otherwise determine data about the UE and to report thedata to another computing device (e.g., the base station 106 or thecomputing devices 108 or 110) or to report a determined priority levelassociated with one or more data requests. In some examples, adestination of data or a priority level can be based at least in part onwhether the techniques are implemented as network-based or sender-basedprioritization, and/or where a priority level is determined (e.g., at aUE, at a computing device, etc.).

The reporting component 104 can determine information about anapplication identifier, user preferences, IP addresses, UE state data,and/or machine learned data or priority levels. In some examples, thereporting component 104 can report or determine information associatedwith each data request as it is sent from the UE 200 to a data source.In some examples, the reporting component 104 can report data ordetermine a priority level on any regular or irregular intervals or inresponse to a request from a remote device.

In some examples, the application ID 206 (also referred to as anapplication identifier) can include data indicative of a type ofapplication being executed by the UE. For example, data about theapplication type may indicate that the application is a video streamingapplication, a web browser, a social media application, or any othertype or class of application. In some examples, data about theapplication type may directly identify the specific application beingexecuted by the UE, via an application name, process name, or otherunique identifier.

The application ID 206 may in some cases indicate the particularapplication that generated the data of a data packet or a data request.In some instances, different application identifiers may correspondrespectively to specific applications. Alternatively, applicationidentifiers may correspond to application types, such as video, audio,email, chat, industrial control, etc. An application identifier may alsocorrespond to a server application to which the data packet is destined.

In further examples, the reporting component 104 can determine andreport a user ID (identifier) that can indicate or correspond to acustomer or user profile, such as an individual or organization usingthe device 200 or to whom the device 200 belongs. As another example, auser ID may indicate or correspond to a particular customer account withwhich the device 200 is associated. As yet another example, a user IDmay indicate or correspond to a provider of services with which a datapacket is associated.

In some examples, the user preference(s) 208 can include data indicativeof one more express or inferred user preferences. For example, the userpreference(s) 208 may indicate settings received by the device 200(e.g., via a user interface) comprising express priority indication(s),such as prioritizing a first application over a second application, orfor prioritizing a first application type (e.g., gaming) over a secondapplication type (e.g., streaming or downloading). In some examples, theuser preference(s) 208 may indicate behaviors of a user over time, suchas data indicating that a file that is downloaded is not consumed (e.g.,viewed, played, installed, etc.) until some time after the download iscomplete. In some examples, the user preference(s) 208 can indicate atime period for which a software update is scheduled, which may helpdetermine a priority level associated with downloading such a softwareupdate. In some examples, the user preference(s) 208 may indicate afrequency of checking a download status for a file, which may indicate alevel of interest in the file, and which may accordingly be used todetermine, in part, a priority level associated with a file download.

In some examples, the reporting component 104 may receive an indicationof congestion at a network level and may present an ability for a userto prioritize data requests for different applications. Accordingly, theuser preference(s) 208 may represent preferences that are associatedwith a particular time period, after which the user preferences may beweighted more or less when determining a priority of downlink dataassociated with a data request.

In some examples, the IP (Internet Protocol) address(es) 210 can includedata indicative of a destination IP address associated with a datarequest and/or an IP address associated with a source of data inresponse to the data request. In some examples, an IP address associatedwith a particular data request may be associated with a higher prioritylevel or a lower priority level. In some examples, an IP address may beassociated with a preferred list of IP addresses, which may result in ormay be associated with a higher priority level. In some examples, apreferred list of IP addresses may be defined by a user or provided by acomputing device. In some examples, the IP address(es) 210 can beassociated with one or more domain names (or a fully qualified domainname (FQDN)) for ease of review by a user.

In some examples, the UE state data 212 can include data representingone or more conditions at the UE. In some examples, the UE state data212 can represent data about a display status of the UE, sensor datafrom the UE, an indication that the UE is associated with a low powermode, an amount of power in a battery associated with the UE, a chargestate indication associated with the UE, as well as other factors. TheUE state data 212 can be input or otherwise provided to the machinelearned component 214 (or another model or machine learned componentdiscussed herein) to determine a priority level associated with a datarequest.

In some examples, the data about a display status of the UE may indicatethat a display is active or inactive, such as whether the display isturned on and/or displaying images, or is turned off and/or notdisplaying images. In some examples, data about a display status mayindicate whether the display of the UE is in active use by a user. Forexample, if the display is a touch-sensitive screen, data about thedisplay status may indicate whether touch inputs are being received froma user. In some examples, the data about a display status of the UE canfurther indicate which application(s) are in a foreground of the displayand which application(s) are in a background of the display. In someexamples, data indicative of a high level of interaction with anapplication and a display can increase a priority of data associatedwith the application, while data indicative of a low level ofinteraction with an application or a display can decrease a priority ofdata associated with the application.

In some examples, the sensor data from the UE can include informationfrom cameras, sensors, and/or other input devices of the UE. In someexamples, input devices of the UE may include a front-facing camera,infrared sensor, light sensor, proximity sensor, and/or other sensors.Sensor data may include data captured by such sensors, or data derivedfrom the data captured by the sensors. For example, an operating systemor an application of the UE can be configured to use data captured byfront-facing sensors to perform facial recognition, detect when a faceof a user is oriented toward the display of the UE, and/or when eyes ofthe user are looking at the display. In some examples, data indicativeof an identified user or of a user facing a display can increase apriority level of downlink data associated with one or moreapplications, while data not indicative of those factors can decrease apriority level associated with such downlink data.

In some examples, the machine learned component 214 can include one ormore machine learned models or heuristics that can be used to determinea priority level of downlink data associated with a data request. Forexample, the machine learned component 214 can include weight(s) forvarious factors that can be used to set priority level(s) or likelihoodsand/or determine factors that increase or decrease a priority level, andby how much.

As noted above, a data request may be associated with an application ID206, as well as other data. In some examples, the machine learnedcomponent 214 can be configured with a predefined list of applicationsand/or types of application, along with corresponding indications ofpriority levels (or relative priority levels) associated with specificapplications or types of applications. Accordingly, in such examples,the machine learned component 214 can use information about theapplication type to find a corresponding entry on the predeterminedlist, and determine if the application is associated with a predefinedpriority level for downlink data transmission.

In some examples, the machine learned component 214 can be configured toweight different factors more heavily than other factors, and/orconsider different factors in different orders. For example, if anapplication ID 206 indicates that a first priority level associated withdownlink data, the machine learned component 214 can be configured toweight that factor more heavily than data indicative of a display statusof the UE or whether the application is in a foreground or background ofthe display. Further, the machine learned component 214 may receive anindication of a user preference 208 associated with a data request butmay also determine a relative priority based on a device type, a userID, a subscription type, roaming status, and the like. In some examples,the machine learned component 214 can receive indications regardingwhether a user experience was positive (e.g., a data prioritization wascorrect from the perspective of a user) or was negative (e.g., a dataprioritization was incorrect from the perspective of a user) and mayadjust parameters and/or weights over time to arrive at an optimal modelfor a user or a plurality of users.

In some examples, the processor(s) 202 is a central processing unit(CPU), a graphics processing unit (GPU), both CPU and GPU, or otherprocessing unit or component known in the art. Furthermore, theprocessor(s) 202 may include any number of processors and/or processingcores. The processor(s) 202 is configured to retrieve and executeinstructions from the memory 204.

The memory 204 can also be described as non-transitory computer-readablemedia or machine-readable storage memory, and may include removable andnon-removable media implemented in any method or technology for storageof information, such as computer executable instructions, datastructures, program modules, or other data.

The memory 204 may include, but is not limited to, RAM, ROM, EEPROM,flash memory or other memory technology, CD-ROM, digital versatile discs(DVD) or other optical storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othertangible, physical medium which can be used to store the desiredinformation.

The device 200 also includes additional data storage devices (removableand/or non-removable) such as, for example, magnetic disks, opticaldisks, or tape. Such additional storage is illustrated in FIG. 2 byremovable storage 216 and non-removable storage 218. Tangiblecomputer-readable media can include volatile and non-volatile, removableand non-removable media implemented in any method or technology forstorage of information, such as computer readable instructions, datastructures, program modules, or other data. The memory 204, theremovable storage 216 and the non-removable storage 218 are all examplesof computer-readable storage media. Computer-readable storage mediainclude, but are not limited to, RAM, ROM, EEPROM, flash memory or othermemory technology, CD-ROM, digital versatile discs (DVD),content-addressable memory (CAM), or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can be accessed by the device 200. Anysuch tangible computer-readable media can be part of the device 200.

The memory 204, the removable storage 216, and/or the non-removablestorage 218 may in some cases include storage media used to transfer ordistribute instructions, applications, and/or data. In some cases, thememory 204, the removable storage 216, and/or the non-removable storage218 may include data storage that is accessed remotely, such asnetwork-attached storage that the device 200 accesses over some type ofdata communications network.

In various examples, any or all of the memory 204, the removable storage216, and/or the non-removable storage 218 may store programminginstructions that, when executed, implement some or all of the functionfunctionality described herein.

The device 200 also can include input device(s) 220, such as a keypad, acursor control, a touch-sensitive display, voice input device, etc., andoutput device(s) 222 such as a display, speakers, printers, etc. Thesedevices are well known in the art and need not be discussed at lengthhere.

As illustrated in FIG. 2, the device 200 also includes one or more wiredor wireless transceiver(s) 224. For example, the transceiver(s) 224 caninclude a network interface card (NIC), a network adapter, a LANadapter, or a physical, virtual, or logical address to connect tovarious networks, devices, or components illustrated in figures herein.To increase throughput when exchanging wireless data, the transceiver(s)224 can utilize multiple-input/multiple-output (MIMO) technology. Thetransceiver(s) 224 can comprise any sort of wireless transceiverscapable of engaging in wireless, radio frequency (RF) communication. Thetransceiver(s) 224 can also include other wireless modems, such as amodem for engaging in Wi-Fi, WiMAX, Bluetooth, infrared communication,and the like.

FIG. 3 is a block diagram of a device 300 including components forprioritizing downlink data for a UE based on various factors. In someexamples, the device 300 can be configured to implement some or all ofthe techniques discussed herein.

FIG. 3 shows basic, high-level components of the device 300. Generally,the device 300 may comprise and/or may be implemented in any of variousnetwork components discussed herein, including those componentsillustrated in FIGS. 1 and 2.

In various examples, the device 300 may include processor(s) 302 andmemory 304. Depending on the exact configuration and type of computingdevice, the memory 304 may be volatile (such as RAM), non-volatile (suchas ROM, flash memory, etc.) or some combination of the two. The memory304 may include the prioritization component 114, which may include UEdata 306, network data 308, a packet tagging component 310, and amachine learned component 312. The memory 304 may further includedownlink data 314, and/or queues 116.

In some examples, the prioritization component 114 can includefunctionality to determine a priority level for data packet(s)associated with a data request for a UE. In some examples, theprioritization component 114 may determine a secondary priority levelassociated with a packet, whereby a primary priority is determined by aQCI level associated with a data request. That is, in some case, theprioritization component 114 can prioritize packets associated with asame QCI to optimize transmission of downlink data associated with asingle UE or between transmission of downlink data associated with aplurality of UEs. The prioritization component 114 can determine apriority level based at least in part on the UE data 306, the networkdata 308, the packet tagging component 310, the machine learnedcomponent 312, the downlink data 314, and/or the queue(s) 116.

Further, the prioritization component 114 can perform deep packetinspection on at least a payload portion of a packet to determine anapplication type, an application identifier, source/destination IPaddresses, and the like, associated with such packets, whereby theprioritization component 114 can determine a priority level based atleast in part on deep packet inspection of downlink data (and/or of adata request) associated with a UE.

In some examples, the prioritization component 114 can increase ordecrease a priority level from an initial priority level or a defaultlevel associated with a QCI level associated with a data request. Forexample, a data packet may be associated with a priority level based ona QCI associated with the data packet. As noted herein, in someexamples, the prioritization component 114 can determine a secondarypriority level to be considered in addition to a default priority levelbased on a QCI. In this manner, data packets may be prioritized withrespect to other data packets associated with a same QCI. In otherexamples, the prioritization component 114 can update or determine apriority level that overrides a default priority level associated with aQCI. In some examples, the data packet with a priority level can bereceived by a PDCP layer, which can override a default priority levelassociated with the QCI based on the priority level as determined by theprioritization component 114.

In some examples, the UE data 306 can include data received from thereporting component 104 associated with the UE 102. For example, the UEdata 306 can comprise the application ID 206, the user preference(s)208, the IP address(es) 210, the UE state data 212, and/or any prioritylevels as determined by the machine learned component 214. In someexamples, individual instances of the UE data 306 can be associated witheach data request to reflect a changing state of the UE over time.

In some examples, the network data 308 can include data associated witha state of a network or data based on aggregated data over time. Forexample, the network data 308 can include data about base station(s)associated with geographical areas, base station capabilities (e.g.,LTE/NR capable), network bandwidth availability, delay times, packeterror rates, etc. In some examples, a priority level can be set by theprioritization component 114 to ensure a downlink data rate, to ensurethat packets are delivered within an associated delay budget, and/or toensure that packets are delivered within a threshold amount of anassociated packet error loss rate.

In some examples, the network data 308 can include data indicative ofpriority levels associated with individual applications or data sources.In some examples, the priority level can be based on an aggregated levelof popularity of applications across a plurality of user devices. Forexample, if an application, such as a gaming application, is currentlypopular (e.g., usage is above a threshold level for a threshold level ofuser devices), the network data 308 can indicate that a priority levelof such data can be increased or decreased, depending on specific goals.In some examples a priority level of downlink data associated with anapplication can change over time as applications increase and decreasein popularity.

In some examples, the packet tagging component 310 can includefunctionality to tag packets or to associate packets with a determinedpriority level for downlink data transmission. In some examples, apacket tag may be embedded in a payload of the data packet or in anotherfield (e.g., a header portion) of the data packet. In other examples,such a packet tag may be associated with the data packet in some otherway, such as by routing the packet tag along with the data packet.

In some examples, the machine learned component 312 can include one ormore machine learned models or heuristics that can be used to determinea priority level of downlink data associated with a data request. Forexample, the machine learned component 312 can include weight(s) forvarious factors that can be used to set priority level(s) or likelihoodsand/or determine factors that increase or decrease a priority level, andby how much.

The machine learned component 312 may receive the UE data 306, thenetwork data 308, as well as other data. Based at least in part on theUE data 306 and/or the network data 308, the machine learned component312 can determine corresponding indications of priority levels (orrelative priority levels) associated with data requests. In someexamples, the machine learned component 312 can determine prioritylevels for data requests associated with a same QCI level, and in someexamples, the priority levels may indicate relative priorities for asingle UE or between multiple UEs.

In some examples, the machine learned component 312 can designatepriority levels for packets to be sent via a particular NR base stationor a particular LTE base station.

The machine learned component 312 can be configured to weight differentfactors more heavily than other factors, and/or consider differentfactors in different orders. For example, if the UE data 306 indicatesthat downlink data associated with a particular application has a firstpriority level but that the network data 308 indicates that theapplication is highly popular or has been associated with (in theaggregate) with a second priority level higher than the first prioritylevel, the machine learned component 312 may weigh each factor whendetermining an ultimate priority level.

In some examples, the downlink data 314 can include data received from adata source to be sent to a UE via a downlink transmission. In someexamples, the device 300 can include data pre-cached or stored in alocation closer to an expected data request. For example, for a basestation near a stadium, the downlink data 314 may include sportsreplays, data about local street traffic, or other transportation data.Thus, in some examples, the downlink data 314 can include data stored inan edge of a network to further reduce latency and to improve a Qualityof Experience (QoE) for a user.

In some examples, the queue(s) 116 can include one or more transmissionqueues for transmitting downlink data to a UE. In some examples, thequeue(s) 116 may be associated with a PDCP layer of a base station. Thequeue(s) 116 may transmit data in a first-in first-out manner, or mayalter a transmission time and/or location within a queue based on thepriority level discussed herein. Additional details of the queue(s) arediscussed in the context of FIG. 4.

In some examples, the processor(s) 302 is a central processing unit(CPU), a graphics processing unit (GPU), both CPU and GPU, or otherprocessing unit or component known in the art. Furthermore, theprocessor(s) 302 may include any number of processors and/or processingcores. The processor(s) 302 is configured to retrieve and executeinstructions from the memory 304.

The memory 304 can also be described as non-transitory computer-readablemedia or machine-readable storage memory, and may include removable andnon-removable media implemented in any method or technology for storageof information, such as computer executable instructions, datastructures, program modules, or other data.

The memory 304 may include, but is not limited to, RAM, ROM, EEPROM,flash memory or other memory technology, CD-ROM, digital versatile discs(DVD) or other optical storage, magnetic cassettes, magnetic tape,magnetic disk storage or other magnetic storage devices, or any othertangible, physical medium which can be used to store the desiredinformation.

The device 300 also includes additional data storage devices (removableand/or non-removable) such as, for example, magnetic disks, opticaldisks, or tape. Such additional storage is illustrated in FIG. 3 byremovable storage 316 and non-removable storage 318. Tangiblecomputer-readable media can include volatile and non-volatile, removableand non-removable media implemented in any method or technology forstorage of information, such as computer readable instructions, datastructures, program modules, or other data. The memory 304, theremovable storage 316 and the non-removable storage 318 are all examplesof computer-readable storage media. Computer-readable storage mediainclude, but are not limited to, RAM, ROM, EEPROM, flash memory or othermemory technology, CD-ROM, digital versatile discs (DVD),content-addressable memory (CAM), or other optical storage, magneticcassettes, magnetic tape, magnetic disk storage or other magneticstorage devices, or any other medium which can be used to store thedesired information and which can be accessed by the device 300. Anysuch tangible computer-readable media can be part of the device 300.

The memory 304, the removable storage 316, and/or the non-removablestorage 318 may in some cases include storage media used to transfer ordistribute instructions, applications, and/or data. In some cases, thememory 304, the removable storage 316, and/or the non-removable storage318 may include data storage that is accessed remotely, such asnetwork-attached storage that the device 300 accesses over some type ofdata communications network.

In various examples, any or all of the memory 304, the removable storage316, and/or the non-removable storage 318 may store programminginstructions that, when executed, implement some or all of the functionfunctionality described herein.

The device 300 also can include input device(s) 320, such as a keypad, acursor control, a touch-sensitive display, voice input device, etc., andoutput device(s) 322 such as a display, speakers, printers, etc. Thesedevices are well known in the art and need not be discussed at lengthhere.

As illustrated in FIG. 3, the device 300 also includes one or more wiredor wireless transceiver(s) 324. For example, the transceiver(s) 324 caninclude a network interface card (NIC), a network adapter, a LANadapter, or a physical, virtual, or logical address to connect tovarious networks, devices, or components illustrated in figures herein.To increase throughput when exchanging wireless data, the transceiver(s)324 can utilize multiple-input/multiple-output (MIMO) technology. Thetransceiver(s) 324 can comprise any sort of wireless transceiverscapable of engaging in wireless, radio frequency (RF) communication. Thetransceiver(s) 324 can also include other wireless modems, such as amodem for engaging in Wi-Fi, WiMAX, Bluetooth, infrared communication,and the like.

FIG. 4 is a block diagram of a device 400 including various layers of aradio protocol stack including one or more queues for prioritizingdownlink data.

The device 400 can include a Packet Data Convergence Protocol (PDCP)layer 402, a Radio Link Control (RLC) layer 404, a Media Access Control(MAC) layer 406, and a Physical (PHY) layer 408. In some examples, thePDCP layer 402 can include the queue(s) 116, which may include one ormore of a common queue 410, an LTE queue 412, an NR queue 414, a defaultbearer queue 416, a dedicated bearer queue 418, an N-th bearer queue420, and/or a K-th queue 422.

Although illustrated as part of the PDCP layer 402, the queue(s) 116 maybe implemented as another component that is communicatively coupled withthe PDCP layer 402.

In some examples, packets received by the PDCP layer 402, which wouldotherwise be queued in a single transmission queue corresponding toInternet data, are instead routed by the PDCP layer 402 into one of thequeue(s) 116, depending on priority data and implementations.

In an example where the queue(s) 116 comprise the LTE queue 412 and theNR queue 414, data packets may be designated as an LTE data packet or asan NR data packet and assigned to the respective queue to be transmittedaccording to a priority level as discussed herein.

In some examples, data packet associated with a high priority can beinput to the dedicated bearer queue 418 while data packets associatedwith a lower priority can be input to the default bearer queue 416. Insome examples, any number of bearer queues can be implemented in thequeue(s) 116, as illustrated by the Nth bearer queue 420. Similarly, thequeue(s) 116 can include any number of queues, as illustrated by the Kthqueue 422.

In some examples, data packets associated with a same QCI can beassociated with a same queue while data within the queue can betransmitted in accordance with a priority level, as discussed herein. Insome examples, data packets can be prioritized with respect to otherdata packets associated with a same destination UE, and in someexamples, data packets can be prioritized with respect to other datapackets associated with other designation UEs.

In some cases, data packets may be initially stored in a common packetqueue 410 before being moved to one of the queues 410, 412, 414, 416,418, 420, or 422. In some examples, there may only be one queue 410whereby packets are input to the queue 410 based on a priority level orare reordered or removed from the queue 410 based on a priority level.

Data packets from the one of the queues 410, 412, 414, 416, 418, 420, or422 are routed to the RLC layer 404 for subsequent processing by the MAClayer 406 and PHY layer 408 and transmission as downlink data.

In some examples, the device 400 can be implemented in a UE where thetechniques may be applied to uplink data to be sent from the UE to abase station.

In an example where the queue(s) 116 include a high priority queue and alower priority queue, the PDCP layer 402 may apply a timeout mechanismto the data packets of the lower priority queue so that data packetsthat have been in the lower priority queue for a predetermined amount oftime without being transmitted are discarded. In some examples, the PDCPlayer 402 does not apply the timeout mechanism to the data packets ofthe higher priority queue. Accordingly, data packets of the priorityqueue can be discarded as appropriate to manage queue overflow, whilethe data packets of the high priority queue are retained, regardless ofhow long they have been queued.

In an example where data packets associated with different prioritylevels are added to a single queue, packets with a higher priority canbe reordered for transmission before packets associated with a lowerpriority.

In some examples, a priority of a packet can change based on an amountof time that a packet has been in a queue. For example, a priority canincrease as an amount of time a packet has been in a queue increases. Insome examples, a packet that has been in a queue for longer than apredetermined amount of time can be discarded.

FIGS. 5-9 illustrate example processes and sequence diagrams inaccordance with examples of the disclosure. These processes areillustrated as logical flow graphs, each operation of which represents asequence of operations that can be implemented in hardware, software, ora combination thereof. In the context of software, the operationsrepresent computer-executable instructions stored on one or morecomputer-readable storage media that, when executed by one or moreprocessors, perform the recited operations. Generally,computer-executable instructions include routines, programs, objects,components, data structures, and the like that perform particularfunctions or implement particular abstract data types. The order inwhich the operations are described is not intended to be construed as alimitation, and any number of the described operations can be combinedin any order, omitted, and/or performed in parallel to implement theprocesses.

FIG. 5 shows a sequence diagram 500 of example operations and messagesfor network-based data packet prioritization for downlink transmission.

The UE 102 can have an active connection between the UE 102 and the basestation 106. In some examples, the connection can be a standaloneconnection or a dual connectivity connection.

At point 502, the UE can send a data request to the base station 106. Atthe same time or in connection with the data request 502, at point 504the UE can send UE attributes to the prioritization component 114. Insome examples, the UE attributes can include an application identifierassociated with the data request 502, an IP address associated with thedata request 502, an indication of whether the application is in aforeground or background, user preferences, and the like, as discussedherein. In some examples, the UE attributes can include a proposedpriority level associated with the data request 502.

At point 506, the prioritization component 114 can determine prioritydata to be associated with the data request 502. In some examples, theprioritization component 114 can determine the priority data based atleast in part on the UE attributes, network attributes, etc. Forexample, the prioritization component 114 use an application identifierassociated with the data request 502 to look up a priority level in adatabase (or other data structure) to determine the priority data. Insome examples, the prioritization component 114 can input UE attributes,network data, etc. into a machine learned model to determine a prioritylevel associated with the data request 502.

At point 508, the prioritization component 114 can provide or otherwisesend the priority data to the base station 106.

In some examples, the UE 102 may include the prioritization component114, in which case the UE 102 would determine a priority level andinclude the priority level as data sent to the base station 106.

At point 510, the base station can forward the data request 502 or cansend a data request based on the data request to the computing device110. In this examples, the computing device 110 represents a data sourceassociated with the data request 502.

At point 512, the computing device 110 can provide data in response tothe data request(s) 502 and 510. The base station 106 can receive thedata sent by the computing device.

At point 514 the base station 106 can update headers (or a portion of aheader) associated with the data response 512 based on the priority data508. In some examples, a PDCP layer of the base station 106 can update aheader of a data packet, add a tag to a data packet, or otherwiseassociated data packets with a priority level, as discussed herein. Insome examples, data packets can be associated with a priority level byassigning the data packets to a particular transmission queue associatedwith the priority level.

At point 516, the base station 106 can send the data to the UE 102 inaccordance with the priority level. In some examples, sending the datafrom the base station 106 to the UE 102 can include sending data packetsprioritized in the PDCP layer to other layers of the radio protocolstack for subsequent transmission to the UE 102.

FIG. 5 accordingly shows operations and messages in a situation in whichnetwork-based prioritization of downlink data transmission isimplemented in a network. In some examples, aspects of FIG. 5 can beperformed in parallel or multiple times in connection with each datarequest associated with a UE. That is, in some examples, multiplepriority levels can be determined for a single UE and various prioritylevels can be determined for respective data. Accordingly, the describedtechniques enhance network functionality and user experience bycustomizing the transmission of data to provide the most appropriateperformance characteristics for any particular application or customer.

FIG. 6 shows a sequence diagram 600 of example operations and messagesfor sender-based data packet prioritization for downlink transmission.

The UE 102 can have an active connection between the UE 102 and the basestation 106. In some examples, the connection can be a standaloneconnection or a dual connectivity connection.

At point 602, the UE can send a data request to the base station 106. Atthe same time or in connection with the data request 602, at point 604the UE can send UE attributes to the prioritization component 114. Insome examples, the UE attributes can include an application identifierassociated with the data request 602, an IP address associated with thedata request 602, an indication of whether the application is in aforeground or background, user preferences, and the like, as discussedherein. In some examples, the UE attributes can include a proposedpriority level associated with the data request 602.

At point 606, the prioritization component 114 can determine prioritydata to be associated with the data request 602. In some examples, theprioritization component 114 can determine the priority data based atleast in part on the UE attributes, network attributes, etc. Forexample, the prioritization component 114 use an application identifierassociated with the data request 602 to look up a priority level in adatabase (or other data structure) to determine the priority data. Insome examples, the prioritization component 114 can input UE attributes,network data, etc. into a machine learned model to determine a prioritylevel associated with the data request 602.

At point 608, the prioritization component 114 can provide or otherwisesend the priority data to the computing device 110. In some examples,the priority data 608 can comprise a unique code or identifier that isseemingly an arbitrary tag or code such that data packets associatedwith the unique code or identifier can be decoded or translated into apriority level by the base station 106. In such an example, theprioritization component 114 can send an indication of the prioritydata, unique code, or identifier to the base station 106 so that thebase station 106 can decode, tag, or otherwise associate particular datapackets with a particular priority level.

In some examples, the UE 102 may include the prioritization component114, in which case the UE 102 would determine a priority level andinclude the priority level as data sent to the computing device 110.

At point 610, the base station 106 can forward the data request 602 orcan send a data request based on the data request 602 to the computingdevice 110. In this example, the computing device 110 represents a datasource associated with the data request 602.

At point 612 the computing device 110 can generate headers for datapackets to be sent in response to the data request 602. In someexamples, the headers can be a field of a TCP/IP data packet header. Insome examples, the computing device 110 can associate data packets withan identifier that can be used by the base station 106 to determine apriority level associated with the data packets responsive to the datarequest 610.

At point 614, the computing device 110 can provide data to the basestation 106 in response to the data request(s) 602 and 610. The basestation 106 can receive the data sent by the computing device 110.

In some examples, a PDCP layer of the base station 106 can receive thedata sent in the data response 610 and can further update a header of adata packet, add a tag to a data packet, or otherwise associated datapackets with a priority level, as discussed herein. In some examples,data packets can be associated with a priority level by assigning thedata packets to a particular transmission queue associated with thepriority level.

At point 616, the base station 106 can send the data to the UE 102 inaccordance with the priority level. In some examples, sending the datafrom the base station 106 to the UE 102 can include sending data packetsprioritized in the PDCP layer to other layers of the radio protocolstack for subsequent transmission to the UE 102.

FIG. 6 accordingly shows operations and messages in a situation in whichsender-based prioritization of downlink data transmission is implementedin a network. In some examples, aspects of FIG. 6 can be performed inparallel or multiple times in connection with each data requestassociated with a UE. That is, in some examples, multiple prioritylevels can be determined for a single UE and various priority levels canbe determined for respective data. Accordingly, the described techniquesenhance network functionality and user experience by customizing thetransmission of data to provide the most appropriate performancecharacteristics for any particular application or customer.

FIG. 7 illustrates an example process 700 for network-based data packetprioritization for downlink transmission. The example process 700 can beperformed (at least in part) by the base station 106, the computingdevices 108 and 110, or by any device comprising the prioritizationcomponent 114, as discussed herein.

At operation 702, the process can include receiving first data from auser equipment (UE), wherein the first data is associated with a datarequest. In some examples, the first data can include UE attributes, asdiscussed herein, although in some examples, the UE attributes can besent separate from the data request.

At operation 704, the process can include inputting the data request, anapplication ID, and/or UE attributes to a machine learned model todetermine a priority level. As discussed herein, the priority level isto be used in prioritizing downlink data transmissions from a basestation to the UE. The priority level can be based on an applicationidentifier, whether an application is in a foreground or background,deep packet inspection including a determining regarding a type of datathat is included in a payload portion of a data packet, userpreferences, network data and conditions, and the like.

At operation 706, the process can include receiving, based at least inpart on the data request, second data. For example, if the data requestis associated with a content stream, such as music or video, the seconddata can include the audio data or the video data. If the data requestis in connection with a gaming application, the second data can comprisea next frame or updated state information associated with the gamingapplication. As can be understood, virtually any type of data can beprovided in response to a data request, and the examples discussedherein are not intended to be exhaustive or limiting.

At operation 708, the process can include assigning the priority levelto packets associated with the second data. In this network-basedprioritization implementation, a base station, or a PDCP layer of theradio protocol stack, can assigning the priority level to packets byupdating a header, a tag, or otherwise associating the data packets witha priority level.

At operation 710, the process can include inputting the packets to aPDCP layer to be sent to the UE based at least in part on the prioritylevel. In some examples, the priority level can be determined by thePDCP layer or by inputting the data packets to a particular queueassociated with a priority level. In such examples, the operation 710can include forwarding, providing, or otherwise sending the data packetsassociated with a priority level to other layers of the radio protocolstack, such as an RLC layer, a MAC layer, or a PHY layer, as discussedherein.

FIG. 8 illustrates an example process 800 for sender-based data packetprioritization for downlink transmission. The example process 800 can beperformed (at least in part) by the base station 106, the computingdevices 108 and 110, or by any device comprising the prioritizationcomponent 114, as discussed herein.

At operation 802, the process can include receiving first data from auser equipment (UE), wherein the first data is associated with a datarequest. In some examples, the first data can include UE attributes, asdiscussed herein, although in some examples, the UE attributes can besent separate from the data request.

At operation 804, the process can include inputting the data request, anapplication ID, and/or UE attributes to a machine learned model todetermine a priority level. As discussed herein, the priority level isto be used in prioritizing downlink data transmissions from a basestation to the UE. The priority level can be based on an applicationidentifier, whether an application is in a foreground or background,deep packet inspection including a determining regarding a type of datathat is included in a data packet, user preferences, network data andconditions, and the like.

At operation 806, the process can include sending second data indicativeof the priority level to a data source associated with the data request.In some examples, the priority data can comprise a unique code oridentifier that is seemingly an arbitrary tag or code such that datapackets associated with the unique code or identifier can be decoded ortranslated into a priority level when received by a base station.

At operation 808, the process can include receiving, based on the datarequest and the second data, third data comprising a packet associatedwith the priority level. As noted above, in some examples, data packetsfrom a data source can be encoded, tagged, or associated with a headerindicative of a unique code or identifier that may be be decoded,converted, or otherwise transformed to a priority level after such datais received by a base station.

At operation 810, the process can include providing, based on thepriority level, packets to a Packet Data Convergence Protocol (PDCP)layer of a base station to be sent to the UE. In some examples, thepriority level can be determined by the PDCP layer or by inputting thedata packets to a particular queue associated with a priority level. Insuch examples, the operation 810 can include forwarding, providing, orotherwise sending the data packets associated with a priority level toother layers of the radio protocol stack, such as an RLC layer, a MAClayer, or a PHY layer, as discussed herein.

FIG. 9 illustrates an example process 900 for implementing inter-UEdownlink data prioritization and/or intra-UE downlink dataprioritization. The example process 900 can be performed (at least inpart) by the base station 106, the computing devices 108 and 110, or byany device comprising the prioritization component 114, as discussedherein.

At operation 902, the process can include receiving data to betransmitted to a user equipment (UE). In some examples, the operationcan be in response to a data request sent from a UE to a data source. Insome examples, a priority level can be associated with the data packetsusing the network-based prioritization or the sender-basedprioritization, as discussed herein.

At operation 904, the process can include determining whether data to besent from a base station or other access point is above a threshold. Insome examples, the operation 904 can include determining whether thebase station is experiencing congestion or is otherwise limited withrespect to some capability. For example, the operation 904 can includedetermining whether a latency is above a threshold, whether a packeterror loss is above a threshold, and the like. If the data (or othermetric) is not above the threshold (“no” in the operation 904), theprocess can continue to operation 906. Such a “no” determination in theoperation 904 may be indicative of an uncongested or unrestrictedtransmission interval or time period associated with a base station.

At operation 906, the process can include implementing intra-UEpriority. In some examples, such intra-UE priority corresponds toprioritizing data packets relative to other data packets addressed tothe same UE. That is, intra-UE priority can include prioritizing data toa UE associated with multiple data requests, as discussed herein.

If the data (or other metric is not above the threshold (“yes” in theoperation 904), the process can continue to operation 908. Such a “yes”determination in the operation 904 may be indicative of a congested orrestricted state associated with a base station, or other conditionsthat transmission resources to a UE are limited.

At operation 908, the process can include implementing inter-UEpriority. In some examples, such inter-UE priority corresponds toprioritizing data packets relative to other data packets addressed toother UEs. The process can continue to the operation 906 to implementintra-UE priority in addition to inter-UE priority.

Although not illustrated in the flow of FIG. 9, in some examples,inter-UE priority may be implemented without implementing intra-UEpriority where by downlink data to be transmitted to a UE is transmittedbased on an order that data packets are received by a base station (andany default priority levels).

At operation 910, the process can include queuing data to be transmittedbased on the inter/intra UE priority, as discussed herein. Accordingly,the described techniques enhance network functionality and userexperience by customizing the transmission of data to provide the mostappropriate performance characteristics for any particular applicationor customer either between data associated with a single UE or betweendata to be transmitted to a plurality of UEs.

EXAMPLE CLAUSES

A: A method comprising: receiving, from a user equipment (UE), firstdata associated with a data request; determining, based at least in parton the data request, a Quality of Service Class Identifier (QCI)associated with the data request; inputting the first data into a modelto determine a priority level associated with the data request;receiving, based at least in part on the data request, second data froma data source; assigning the QCI and the priority level to packetsassociated with the second data; and providing the packets associatedwith the QCI and the priority level to a Packet Data ConvergenceProtocol (PDCP) layer of a base station, wherein the base station sendsat least a portion of the packets to the UE in accordance with the QCIand the priority level.

B: The method of paragraph A, wherein the model is a machine learnedmodel trained to determine the priority level based at least in part onattributes associated with the UE and on the data source.

C: The method of paragraph A or B, wherein the first data comprises anapplication identifier and an indication of whether an applicationassociated with the application identifier is in a foreground or abackground associated with the UE.

D: The method of any of paragraphs A-C, wherein the first data comprisesan indication received via a user interface associated with the UE,wherein the indication comprises at least one user preference.

E: The method of any of paragraphs A-D, wherein: the data request is afirst request, the priority level is a first priority level, the datasource is a first data source, the packets are first packets, and themethod further comprising: receiving, from the UE, third data associatedwith a second data request; determining that the second data request isassociated with the QCI; inputting the third data into the model todetermine a second priority level associated with the second datarequest; receiving, based at least in part on the second data request,fourth data from a second data source; assigning the QCI and the secondpriority level to second packets associated with the fourth data; andproviding the second packets associated with the QCI and the secondpriority level to PDCP layer of the base station, wherein the basestation sends the second packets to the UE in accordance with the QCIand the second priority level.

F: The method of paragraph E, wherein the second packets are prioritizedover the first packets based at least in part on the first prioritylevel and the second priority level.

G: The method of any of paragraphs A-F, further comprising: determiningthe priority level based at least in part on a payload portion of apacket associated with the second data.

H: The method of any of paragraphs A-G, wherein: the packets are firstpackets; the UE is a first UE; and the priority level prioritizes thefirst packets with respect to second packets associated with a secondUE.

I: The method of any of paragraphs A-H, wherein: the packets are firstpackets associated with the UE; and the priority level prioritizes thefirst packets with respect to second packets associated with the UE.

J: A system comprising: one or more processors; and one or morenon-transitory computer-readable media storing computer-executableinstructions that, when executed, cause the one or more processors toperform operations comprising: receiving, from a user equipment (UE),first data associated with a data request; determining, based at leastin part on the data request, a Quality of Service Class Identifier (QCI)associated with the data request; inputting the first data into a modelto determine a priority level associated with the data request;receiving, based at least in part on the data request, second data froma data source; assigning the QCI and the priority level to packetsassociated with the second data; and providing the packets associatedwith the QCI and the priority level to a Packet Data ConvergenceProtocol (PDCP) layer of a base station, wherein the base station sendsat least a portion of the packets to the UE in accordance with the QCIand the priority level.

K: The system of paragraph J, wherein the model is a machine learnedmodel trained to determine the priority level based at least in part onattributes associated with the UE and on the data source.

L: The system of paragraph J or K, wherein the first data comprises anapplication identifier and an indication of whether an applicationassociated with the application identifier is in a foreground or abackground associated with the UE.

M: The system of any of paragraphs J-L, the operations furthercomprising: determining the priority level based at least in part on apayload portion of a packet associated with the second data.

N: The system of any of paragraphs J-M, wherein: the packets are firstpackets; the UE is a first UE; and the priority level prioritizes thefirst packets with respect to second packets associated with a secondUE.

O: The system of paragraph N, wherein: wherein the first packets and thesecond packets are associated with a same Quality of Service (QoS) ClassIdentifier (QCI).

P: The system of any of paragraphs J-O, wherein: the packets are firstpackets associated with the UE; and the priority level prioritizes thefirst packets with respect to second packets associated with the UE.

Q: One or more non-transitory computer-readable media storingcomputer-executable instructions that, when executed, cause one or moreprocessors to perform operations comprising: receiving first data from auser equipment (UE), the first data associated with a data request;inputting at least one of the data request, an application identifierassociated with the data request, or attribute data associated with theUE to a machine learned model; receiving, from the machine learnedmodel, a priority level associated with the data request; receiving,based at least in part on the data request, second data; updating, basedat least in part on the priority level, a header associated with apacket of the second data; and inputting the packet to a Packet DataConvergence Protocol (PDCP) layer of a base station to send the packetto the UE.

R: The one or more non-transitory computer-readable media of paragraphQ, the operations further comprising: receiving, from the UE, theapplication identifier and the attribute data; and inputting the datarequest, the application identifier, and the attribute data to themachine learned model; wherein the priority level is based at least inpart on the data request, the application identifier, and the attributedata.

S: The one or more non-transitory computer-readable media of paragraphR, wherein the attribute data is based at least in part on an indicationfrom a user.

T: The one or more non-transitory computer-readable media of any ofparagraphs Q-S, wherein: the packet is a first packet; the UE is a firstUE; the priority level prioritizes the first packet with respect to asecond packet associated with a second UE; and the first packet and thesecond packet are associated with a same Quality of Service (QoS) ClassIdentifier (QCI).

U: A method comprising: receiving, from a user equipment (UE), firstdata associated with a data request; determining, based at least in parton the data request, a Quality of Service Class Identifier (QCI)associated with the data request; inputting the first data into a modelto determine a priority level associated with the data request; sendingsecond data indicative of the priority level to a data source associatedwith the data request; receiving, based at least in part on the seconddata and the data request, third data from the data source, the thirddata comprising a packet with a header portion comprising an indicationof the priority level; and providing, based at least in part on thepriority level, packets associated with the third data to a Packet DataConvergence Protocol (PDCP) layer of a base station, wherein the basestation sends the packets to the UE in accordance with the QCI and thepriority level.

V: The method of paragraph U, further comprising: establishing, based atleast in part on the QCI, a bearer associated with the UE; and providingthe packets to the PDCP layer further based at least in part on the QCI.

W: The method of paragraph U or V, wherein the model is a machinelearned model trained to determine the priority level based at least inpart on attributes associated with the UE and on the data source.

X: The method of any of paragraphs U-W, wherein the first data comprisesan application identifier and an indication of whether an applicationassociated with the application identifier is in a foreground or abackground associated with the UE.

Y: The method of any of paragraphs U-X, wherein the first data comprisesan indication received via a user interface associated with the UE,wherein the indication comprises at least one user preference.

Z: The method of any of paragraphs U-Y, wherein: the data request is afirst request, the priority level is a first priority level, the datasource is a first data source, the packet is a first packet, the headerportion is a first header portion, the packets are first packets, andthe method further comprising: receiving, from the UE, fourth dataassociated with a second data request; determining that the second datarequest is associated with the QCI; inputting the fourth data into themodel to determine a second priority level associated with the seconddata request; sending fifth data indicative of the second priority levelto a second data source associated with the second data request;receiving, based at least in part on the fifth data and the second datarequest, sixth data from the second data source, the sixth datacomprising a second packet with a second header portion comprising anindication of the second priority level; and providing, based at leastin part on the second priority level, second packets associated with thesixth data to the PDCP layer of the base station, wherein the basestation sends the second packets to the UE in accordance with the QCIand the second priority level.

AA: The method of paragraph Z, wherein the second packets areprioritized over the first packets based at least in part on the firstpriority level and the second priority level.

AB: The method of any of paragraphs U-AA, wherein providing the packetsassociated with the third data to the PDCP layer overrides a defaultpriority level associated with the QCI.

AC: A system comprising: one or more processors; and one or morenon-transitory computer-readable media storing computer-executableinstructions that, when executed, cause the one or more processors toperform operations comprising: receiving, from a user equipment (UE),first data associated with a data request; determining, based at leastin part on the data request, a Quality of Service Class Identifier (QCI)associated with the data request; inputting the first data into a modelto determine a priority level associated with the data request; sendingsecond data indicative of the priority level to a data source associatedwith the data request; receiving, based at least in part on the seconddata and the data request, third data from the data source, the thirddata comprising a packet with a header portion comprising an indicationof the priority level; and providing, based at least in part on thepriority level, packets associated with the third data to a Packet DataConvergence Protocol (PDCP) layer of a base station, wherein the basestation sends the packets to the UE in accordance with the QCI and thepriority level.

AD: The system of paragraph AC, the operations further comprising:establishing, based at least in part on the QCI, a bearer associatedwith the UE; and providing the packets to the PDCP layer further basedat least in part on the QCI.

AE: The system of paragraph AC or AD, wherein the model is a machinelearned model trained to determine the priority level based at least inpart on attributes associated with the UE and on the data source.

AF: The system of any of paragraphs AC-AE, wherein the first datafurther comprises an application identifier.

AG: The system of paragraph AF, wherein the first data further comprisesan indication of whether an application associated with the applicationidentifier is in a foreground or a background associated with the UE.

AH: The system of any of paragraphs AC-AG, wherein providing the packetsassociated with the third data to the PDCP layer overrides a defaultpriority level associated with the QCI.

AI: The system of any of paragraphs AC-AH, wherein: the packets arefirst packets; the base station is a first base station; the PDCP layeris a first PDCP layer; and the operations further comprise: sendingsecond packets associated with the third data to a second PDCP layer ofa second base station to be transmitted by the second base station tothe UE.

AJ: The system of any of paragraphs AC-AI, wherein: the packets arefirst packets associated with the UE; and the priority level prioritizesthe first packets with respect to second packets associated with the UE.

AK: One or more non-transitory computer-readable media storingcomputer-executable instructions that, when executed, cause one or moreprocessors to perform operations comprising: receiving first data from auser equipment (UE), the first data associated with a data request;inputting at least one of the data request, an application identifierassociated with the data request, or attribute data associated with theUE to a machine learned model; receiving, from the machine learnedmodel, a priority level associated with the data request; sending seconddata indicative of the priority level to a data source associated withthe data request; receiving, based at least in part on the data requestand the second data, third data comprising a packet associated with thepriority level; and providing, based at least in part on the prioritylevel, packets to a Packet Data Convergence Protocol (PDCP) layer of abase station to be sent to the UE.

AL: The one or more non-transitory computer-readable media of paragraphAK, the operations further comprising: receiving, from the UE, theapplication identifier and the attribute data; and inputting the datarequest, the application identifier, and the attribute data to themachine learned model; wherein the priority level is based at least inpart on the data request, the application identifier, and the attributedata.

AM: The one or more non-transitory computer-readable media of paragraphAK or AL, wherein the priority level is associated with at least one ofa downlink data rate, a delay budget, or a packet error loss rate.

AN: The one or more non-transitory computer-readable media of any ofparagraphs AK-AM, the operations further comprising: determining that acongestion level meets or exceeds a threshold level; and providing thepackets to the PDCP layer based at least in part on the congestion levelmeeting or exceeding the threshold level.

While the example clauses described above are described with respect toone particular implementation, it should be understood that, in thecontext of this document, the content of the example clauses can also beimplemented via a method, device, system, computer-readable medium,and/or another implementation. Additionally, any of examples A-AN may beimplemented alone or in combination with any other one or more of theexamples A-AN.

CONCLUSION

Although features and/or methodological acts are described above, it isto be understood that the appended claims are not necessarily limited tothose features or acts. Rather, the features and acts described aboveare disclosed as example forms of implementing the claims.

What is claimed is:
 1. A method comprising: receiving, from a userequipment (UE), first data associated with a data request; determining,based at least in part on the data request, a Quality of Service ClassIdentifier (QCI) associated with the data request; inputting the firstdata into a model to determine a priority level associated with the datarequest; sending second data indicative of the priority level to a datasource associated with the data request; receiving, based at least inpart on the second data and the data request, third data from the datasource, the third data comprising a packet with a header portioncomprising an indication of the priority level; and providing, based atleast in part on the priority level, packets associated with the thirddata to a Packet Data Convergence Protocol (PDCP) layer of a basestation, wherein the base station sends the packets to the UE inaccordance with the QCI and the priority level.
 2. The method of claim1, further comprising: establishing, based at least in part on the QCI,a bearer associated with the UE; and providing the packets to the PDCPlayer further based at least in part on the QCI.
 3. The method of claim1, wherein the model is a machine learned model trained to determine thepriority level based at least in part on attributes associated with theUE and on the data source.
 4. The method of claim 1, wherein the firstdata comprises an application identifier and an indication of whether anapplication associated with the application identifier is in aforeground or a background associated with the UE.
 5. The method ofclaim 1, wherein the first data comprises an indication received via auser interface associated with the UE, wherein the indication comprisesat least one user preference.
 6. The method of claim 1, wherein: thedata request is a first request, the priority level is a first prioritylevel, the data source is a first data source, the packet is a firstpacket, the header portion is a first header portion, the packets arefirst packets, and the method further comprising: receiving, from theUE, fourth data associated with a second data request; determining thatthe second data request is associated with the QCI; inputting the fourthdata into the model to determine a second priority level associated withthe second data request; sending fifth data indicative of the secondpriority level to a second data source associated with the second datarequest; receiving, based at least in part on the fifth data and thesecond data request, sixth data from the second data source, the sixthdata comprising a second packet with a second header portion comprisingan indication of the second priority level; and providing, based atleast in part on the second priority level, second packets associatedwith the sixth data to the PDCP layer of the base station, wherein thebase station sends the second packets to the UE in accordance with theQCI and the second priority level.
 7. The method of claim 6, wherein thesecond packets are prioritized over the first packets based at least inpart on the first priority level and the second priority level.
 8. Themethod of claim 1, wherein providing the packets associated with thethird data to the PDCP layer overrides a default priority levelassociated with the QCI.
 9. A system comprising: one or more processors;and one or more non-transitory computer-readable media storingcomputer-executable instructions that, when executed, cause the one ormore processors to perform operations comprising: receiving, from a userequipment (UE), first data associated with a data request; determining,based at least in part on the data request, a Quality of Service ClassIdentifier (QCI) associated with the data request; inputting the firstdata into a model to determine a priority level associated with the datarequest; sending second data indicative of the priority level to a datasource associated with the data request; receiving, based at least inpart on the second data and the data request, third data from the datasource, the third data comprising a packet with a header portioncomprising an indication of the priority level; and providing, based atleast in part on the priority level, packets associated with the thirddata to a Packet Data Convergence Protocol (PDCP) layer of a basestation, wherein the base station sends the packets to the UE inaccordance with the QCI and the priority level.
 10. The system of claim9, the operations further comprising: establishing, based at least inpart on the QCI, a bearer associated with the UE; and providing thepackets to the PDCP layer further based at least in part on the QCI. 11.The system of claim 9, wherein the model is a machine learned modeltrained to determine the priority level based at least in part onattributes associated with the UE and on the data source.
 12. The systemof claim 9, wherein the first data further comprises an applicationidentifier.
 13. The system of claim 12, wherein the first data furthercomprises an indication of whether an application associated with theapplication identifier is in a foreground or a background associatedwith the UE.
 14. The system of claim 9, wherein providing the packetsassociated with the third data to the PDCP layer overrides a defaultpriority level associated with the QCI.
 15. The system of claim 9,wherein: the packets are first packets; the base station is a first basestation; the PDCP layer is a first PDCP layer; and the operationsfurther comprise: sending second packets associated with the third datato a second PDCP layer of a second base station to be transmitted by thesecond base station to the UE.
 16. The system of claim 9, wherein: thepackets are first packets associated with the UE; and the priority levelprioritizes the first packets with respect to second packets associatedwith the UE.
 17. One or more non-transitory computer-readable mediastoring computer-executable instructions that, when executed, cause oneor more processors to perform operations comprising: receiving firstdata from a user equipment (UE), the first data associated with a datarequest; inputting at least one of the data request, an applicationidentifier associated with the data request, or attribute dataassociated with the UE to a machine learned model; receiving, from themachine learned model, a priority level associated with the datarequest; sending second data indicative of the priority level to a datasource associated with the data request; receiving, based at least inpart on the data request and the second data, third data comprising apacket associated with the priority level; and providing, based at leastin part on the priority level, packets to a Packet Data ConvergenceProtocol (PDCP) layer of a base station to be sent to the UE.
 18. Theone or more non-transitory computer-readable media of claim 17, theoperations further comprising: receiving, from the UE, the applicationidentifier and the attribute data; and inputting the data request, theapplication identifier, and the attribute data to the machine learnedmodel; wherein the priority level is based at least in part on the datarequest, the application identifier, and the attribute data.
 19. The oneor more non-transitory computer-readable media of claim 17, wherein thepriority level is associated with at least one of a downlink data rate,a delay budget, or a packet error loss rate.
 20. The one or morenon-transitory computer-readable media of claim 17, the operationsfurther comprising: determining that a congestion level meets or exceedsa threshold level; and providing the packets to the PDCP layer based atleast in part on the congestion level meeting or exceeding the thresholdlevel.